Unlocking Knowledge From Text & Social Media

WASHINGTON, D.C. -- Text and social media analytics could offer significant value across federal government agencies and departments, and should be considered essential for regulators and lawmakers who want to stay on top of emerging trends.

That was the takeaway from a panel of experts from government, academia, and industry who gathered to discuss the art of the possible -- what people are doing and how they are using text and social media analytics -- at the 2013 SAS Government Leadership Summit. And while they cautioned that "we're not quite there yet" in terms of extracting knowledge from this data, they stressed that tools are rapidly evolving that could help the government turn information into action in the near future.

A panel discussion on text and social media analytics drew a large crowd.

John Cassara, a former US Treasury special agent, author of several books on money laundering, and an industry adviser to SAS Federal LLC, discussed social media analytics as it relates to financial crime investigations and terror financing.

"Normally, when I speak, I like to share a few war stories. But this, the use of text and social media analytics, is so new there is very, very little out there in the public domain. However, it is possible, and we're moving toward it," he said, adding that the current use and analysis of social media within the US government "depends greatly on the agencies and departments and their internal procedures."

Although he cautioned that it is "no silver bullet" and raises still unresolved issues about privacy and civil liberties, Cassara predicted text and social media analytics will become an "important tool in the law enforcement toolbox."

Denise Bedford, Goodyear Professor of Knowledge Management at the College of Communication and Information at Kent State University and former senior information officer at the World Bank in Washington, D.C., explained how text analytics can create efficiencies in the ways information is defined, organized, and accessed -- delivering measurable and meaningful improvements in performance.

In recent years, she explained, there have been significant advances in the ways knowledge from text is extracted and validated, making it a better and more reliable source of information. "You can test your subjective opinions, develop objective models, and quantify ideas," she explained.

But Lieutenant Colonel Eric Hansen, retired from the US Army Military Intelligence Corps and now an engineering support manager at SAS, cautioned that just because something appears on social media does not make it relevant. "The challenge is using this information properly, so it is both efficient and informative," he said.

Tom Sabo, senior solutions architect at SAS, called social media "another signal" of impending events -- from disease outbreaks to economic trends. Sabo, who describes himself on Twitter as a "cognitive/computer scientist navigating the world of text analytics, government, and social media," stressed that opportunities for innovation abound -- from gauging public sentiment, influencing opinion, and shaping policy, to proactively identifying and reacting to shifting market, political, or social trends.

How much value do you think lawmakers and federal regulators can extract from free-form text in everything from social media, reports, comments, email, abstracts, and survey data? Could this data provide additional signals on emerging trends and potential threats?

Noreen Seebacher,

Noreen Seebacher, the Community Editor of Investor Uprising, has been a business journalist for more than 20 years. A New York City based writer and editor, she has worked for numerous print and online publications. Her work has appeared in The New York Times, the New York Post, New York’s Daily News, The Detroit News, and the Pittsburgh Press. She co-edited five newsletters for Real Estate Media’s GlobeSt.com and served as the site's technology editor.

She also championed the commercial real estate beat at The Journal News, a Gannett publication in suburban New York City, and co-founded a Website focused on personal finance. Through her own company, Stasa Media, Noreen has produced reports, whitepapers, and internal publications for a number of Fortune 500 clients. When she's not writing, editing, or Web surfing, she relaxes in an 1875 Victorian with her husband and their five kids, four formerly homeless cats, and a dog.

Natural languages are highly ambiguous. It is commonly known in natural language processing that a simple sentence (or word) can have many different interpretations. Sometime only the knowledge of the state of the world can help resolve the ambiguity. In the case of " #nowthatcherisdead", we need more information (that is out of the text itself) in order get the meaning of the text.